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Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Data Science at Stripe is a vibrant community where data analysts and data scientists learn and grow together. You'll work with some of the most fundamental data at Stripe, and use that data to help drive company-wide initiatives. We have a variety of Data Analytics roles and teams across Stripe and will seek to align you to the most relevant team based on your background. What you'll do In this role, you'll partner deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. You'll work closely with partners to extract insights from the rich and complex data at Stripe. You'll also work with leaders to translate business needs into data problems. You'll build metrics, scalable data pipelines, dashboards, and reports to inform and run the business. You'll deliver actionable business recommendations through analyses and data storytelling. Who you are We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. Minimum requirements MS/MA + 2 years or BS/BA + 3 years of full-time experience exclusive of internships in Business Intelligence Engineering, Data Analyst, and Business Analyst roles Proficiency in SQL Proven ability to manage and deliver on multiple projects with great attention to detail Ability to clearly communicate results and drive impact Ability to design, implement, and maintain data pipelines and dashboards to generate actionable insights based on stakeholder requirements Experience collaborating with cross-functional teams to deliver strategic insights, benchmarks, and analyses that provide recommendations Ability to enable stakeholders and partners by building self-service tooling and providing training to empower stakeholder teams to be data literate and self-sufficient in autonomous reporting capabilities Preferred qualifications Prior experience at a growth-stage internet or software company Experience with distributed data frameworks like Spark to write and debug data pipelines Good understanding of development processes and best practices like engineering standards, code reviews, and testing Strong statistical knowledge Working knowledge of Python Experience creating leadership-level reporting, such as QBRs, MBRs Proficiency with AI tools to accelerate model development, analysis, and coding
Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team As Stripe’s user base and global footprint grow dramatically, we have distinctly unique support problems resulting from both our type of scale and the type of businesses we partner with. The Stripe Delivery Center (SDC) strategy will provide operational leverage and expand Stripe’s portfolio of operational capabilities to support the scaled needs of external users and internal Stripe teams. At Stripe, our Mexico City office is a vibrant hub at the forefront of our mission to reshape the financial landscape for businesses worldwide. Our team prioritizes collaboration, innovation, and excellence. As a member of the Mexico City team, you'll be part of a mission-driven community dedicated to enhancing the global economy and increasing the GDP of the internet. We strive for excellence by creating with craft and beauty, while having fun and celebrating our successes together. We cultivate a culture of collaboration, inclusivity, and support where every team member’s voice matters. Our commitment shines through as we handle over a million support cases each year, empowering our users not just to solve problems but to achieve their goals. What you’ll do As an analyst on the Payments Health Operations team, you will be charged with monitoring and maintaining payments performance for Stripe’s largest users. This will include triaging, investigating, and responding to detected regressions in authentication and cost rates; providing in-depth analysis of performance degradations; answering queries from our product support and technical account management teams; and engaging with users and other teams at Stripe to help ensure our users are maximizing their acceptance rates while minimizing their costs and fraud. You will work at the core of Stripe's platform, ensuring the reliability of our payments stack and the health of the broader ecosystem. Technical Operations roles in Payments are a dynamic and key component of Stripe's success. Focused on financial partner integrations and funds-flow expansion, we sit at the intersection of product/platform engineers and financial partners, connecting them to ensure that everyone thrives and nothing is lost in translation. Responsibilities Monitor authorization rates and performance for large users, responding to alerts of degradation, triaging and investigating the cause, and communicating your findings to the account team, banking partners, and card networks. Analyze cost checkers to ensure our cost models' accuracy. Respond to performance inquiries from technical account managers, product support teams, and other internal Stripe teams. Interface with Stripe’s financial partners across the world to communicate operational breakages and help drive resolutions. Provide fast, accurate responses to complex support inquiries from partners. Partner with internal and external teams to validate the accuracy of Stripe’s financial data. Introduce data and process efficiencies to meet the scale and speed of Stripe. Identify and automate inefficient operational processes to reduce manual workloads. Who you are We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. Minimum requirements Have at least 1 year of experience in a technical role, with experience writing SQL queries to query relational databases. Have experience navigating the nuanced complexity of financial systems and solving large-scale, technical challenges. Have strong analytical skills to investigate, prioritize, and identify the root cause of issues. Have experience managing communications and workflows with technical and non-technical teams across internal and external stakeholders. Are comfortable operating independently and thrive in a fast-paced environment to deliver results, with an ability to establish priorities and reliably execute against time-sensitive deadlines. Have experience identifying and triaging technical issues. Possess a demonstrated track record of process improvement and proactive problem-solving. Have excellent written and verbal communication skills in both English and Spanish. Preferred qualifications Payments expertise (working with financial partners, optimizing processing errors, managing payment costs). Experience operating in a high-growth technology company. Python or Scala knowledge.
Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Data Science at Stripe is a vibrant community where data analysts and data scientists learn and grow together. You'll work with some of the most fundamental data at Stripe, and use that data to help drive company-wide initiatives. We have a variety of Data Analytics roles and teams across Stripe and Data Analysts are hired in line with the business needs and domain of the organization they will support. What you’ll do In this role, you'll partner deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. You'll design, build, and own the scalable data infrastructure that powers analytics and reporting across the company. Day to day, you'll translate complex business requirements into reliable data models, own end-to-end pipeline development from raw data ingestion to clean, consumption-ready datasets, and work with leaders to prioritize the highest-impact data investments. You'll go beyond building dashboards—you'll architect the data layer that makes self-service analytics possible and deliver actionable business recommendations through rigorous analysis and data storytelling. Responsibilities Design, build, and maintain scalable data pipelines and ETL/ELT workflows that power production-grade financial reporting, risk measurement, and operational decisioning for Treasury Finance Leverage AI tools (code assistants, LLM-based agents) to accelerate pipeline development, data quality automation, reconciliation, and documentation - expanding technical scope while maintaining quality. Model and transform raw data into clean, well-documented datasets that serve as the core foundations for decision making for Treasury Finance (e.g. float positions, cash explainability, risk exposures, liquidity management) Establish and enforce data quality standards through testing, monitoring, and alerting on pipeline health Establish and own data freshness SLAs, operational alerting, and incident response for your data domains - ensuring production reliability for risk and finance critical workflows Partner deeply with Treasury Finance, data scientists/analysts, and engineers to define data requirements and deliver trusted, reusable financial data products Partner deeply with Treasury Finance stakeholders to translate business requirements into data architecture decisions, anticipating needs and helping to drive data strategy rather than reacting to requests Build self-service tooling and analytics layer that empower stakeholders to access and explore trusted data autonomously Who you are We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. Minimum requirements 6+ years of full-time experience in Data Engineering, Analytics Engineering, Business Intelligence Engineering, or a related analytical role Proficiency in SQL, including complex query optimization and data modeling Proficiency in Python for data pipeline development, not just scripting Experience with distributed data frameworks like Spark to write and debug data pipelines Experience with workflow orchestration tools (e.g. Airflow, Flyte, or equivalent) Proven ability to design, implement, and maintain production-grade data pipelines and dashboards Good understanding of development processes and best practices like engineering standards, code reviews, and testing Ability to clearly communicate results and drive impact with cross-functional partners Experience owning production data products with defined quality standards, testing, and documentation Preferred qualifications Prior experience at a growth-stage internet or software company Prior experience working with Finance or Treasury teams Understanding of treasury and finance concepts (e.g., float positions, FX exposure, cash reconciliation, balance sheet usage, liquidity management) Experience with data quality frameworks, data contracts, tiering/classification, or SLA management Experience creating leadership-level reporting, such as QBRs and MBRs Experience building financial reporting infrastructure - e.g. automated treasury processes, regulatory reporting, or finance close Proficiency with AI tools (code assistants, LLM agents) to accelerate pipeline development and data quality automation Interest in how data products enable automated/agentic workflows — understanding that data quality determines the reliability of every downstream decision
Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team The Payments organization owns some of Stripe's most critical payment flows and a platform that processes hundreds of billions of dollars in payments a year. Our team is responsible for translating complex partner specifications related to network costs (interchange and scheme fees) into simplified logic for internal and external consumption. This also drives decisions and product recommendations to manage the underlying network costs paid by Stripe and our users. The team partners closely with the engineering, product, finance, and partnership groups to manage and understand Stripe's network costs. Our work is core to Stripe's business, as Technical Operations roles in Payments are a dynamic and key component of Stripe's success. We sit at the intersection of product and platform engineers and financial partners, connecting them to ensure that everyone thrives and nothing is lost in translation. What you'll do We're looking to add payment enthusiasts who enjoy interpreting complex cost structures and ever-changing payment network systems to optimize on behalf of Stripe and our users. You'll be instrumental in building Stripe's approach to managing our global network cost base. Responsibilities • Collaborate across the company, including engineering, accounting, financial partnerships, and product teams, to analyze billions of dollars moving through the Stripe platform • Translate network specifications into implementation instructions to create billing models for new and revised fees (both scheme and interchange) • Influence product strategy to minimize network costs • Collaborate with Product, Engineering, and Finance to implement cost-saving opportunities, prioritize investment, and explain cost and margin trends • Monitor and maintain the accuracy of the fees through validation and alerting • Create fee explainability to internal and external stakeholders and host education sessions for internal teams to scale knowledge • Introduce data and process efficiencies to meet the scale and speed of Stripe. Identify and automate inefficient operational processes to reduce manual workloads, and scale our network cost operation by driving the design, documentation, and training of operational processes to leverage partner relationships Who you are We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. Minimum requirements • Have 4+ years of experience in Payments at a leading technology or payments company, with the ability to write SQL to query relational databases • Have experience managing communications and workflows with technical and non-technical teams across internal and external stakeholders • Have experience navigating the nuanced complexity of financial systems and solving large-scale, technical challenges • Have strong financial modeling and diagnostic skills to investigate, prioritize, and identify the root cause of issues • Have experience managing multiple, concurrent work streams, identifying and triaging technical issues, and driving solutions with clear metrics to show impact Preferred qualifications • Experience working in fast-paced environments (e.g., high-growth fintech or tech company, management consulting) • Experience mentoring junior team members in technical skill development, operational strategy, and problem solving • Experience working with PM, Engineers, finance team, or accounting team • Experience handling tickets and adhering to operational targets and metrics • Experience with visualization tools
Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team Finance and Strategy Data Science builds the forecasting models, data infrastructure, and analytics tools at the core of how Stripe measures and plans its business. The team owns everything from hierarchical time series and agentic forecasting tools that predict payment volumes and revenue margins, to the governed metrics platform that feeds company-wide dashboards and executive reporting. We partner closely with Finance and Strategy, GTM, and Product stakeholders to directly inform financial decisions across Stripe's entire business. The team combines technical depth, strategic thinking, and executive partnership that develops both technical and business expertise. What you’ll do Data Science Managers at Stripe are responsible for the success of their team. You'll be deeply involved in the modeling and design processes as well as coaching, mentoring, and leading the team. You'll have a deep understanding of how to drive efficient data science teams and you'll have a strong user-focus. You'll be working with data scientists, analysts, and engineers on creating technical solutions and communicating effectively across teams and senior leadership. Responsibilities Drive the roadmap and priorities for your team, and work with many Stripe leaders across the company to enhance our ability to be data-driven. Collaborate with stakeholders across the organization such as engineering, analytics, operations, finance, and marketing. Lead and manage processes to help the team do its best work and engage effectively with the rest of Stripe. Manage a high-performing team of data scientists, supporting them to achieve a high level of technical excellence and advance in their careers. Recruit and onboard great data scientists, in collaboration with Stripe's recruiting team. Contribute to broad data science initiatives as a member of Stripe's data science management team. Who you are We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. Minimum requirements You have at least 3 years of direct management experience leading data science or ML teams, and 10 years of overall data science experience. You've demonstrated expertise in designing metrics and guiding business decisions with data. You have technical expertise to drive clarity with staff and senior scientists about architecture and strategic modeling decisions. You've managed teams that have built and shipped machine learning systems and data products at scale, and have hands-on experience with challenging problems. You work very well cross-functionally, and are able to think rigorously and make hard decisions and tradeoffs. You have clear and persuasive communication skills in writing and in speech. You thrive on a high level of autonomy and responsibility. You foster a healthy, inclusive, challenging, and supportive work environment. Preferred qualifications A PhD or MS in a quantitative field (e.g., Statistics, Operations Research, Economics, Computer Science, Engineering) You're comfortable working with geographically distributed teams. Expertise in time series forecasting, predictive modeling, or optimization Expertise in data design and building scalable data architectures
Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team The Data Science and Analytics organization at Stripe partners with teams across the company to drive rigorous, data-informed decision-making at scale. Within this org, the Verifications and Greater China data teams deliver critical analytical and data science work—from identity verification and risk modeling to market-specific growth insights—that directly shapes Stripe's ability to serve users safely and expand into new markets. Today, the team comprises individual contributors distributed across Singapore and India, supporting two high-impact pillars. We're looking for a founding Data Science Manager based in Bengaluru to build and lead this growing regional footprint from the ground up. What you'll do This is a rare 0 → 1 leadership role with a dual mandate. Pillar 1—Direct Team Leadership • Manage a team of Data Scientists and Data Analysts (currently 4 individual contributors across India and Singapore) spanning the Verifications and Greater China workstreams. • Own roadmap prioritization, execution quality, and stakeholder alignment for both workstreams. • Drive hiring for open and future roles in India, building a high-caliber data team in a competitive talent market. • Foster individual contributor growth through real-time coaching, mentorship, career development, and performance management. Pillar 2—Regional Data Craft Lead (India Office) • Serve as the founding data craft leader for Stripe's India office. Set quality standards, establish community rituals (knowledge sharing, peer reviews, office hours), and cultivate a strong local data culture. • Act as the go-to point of contact for data craft standards, tooling, and best practices for co-located analysts, even those outside your direct reporting line. • Partner with managers and leads across the broader Data org to ensure consistency in methodology, tooling, and quality bar. • Support onboarding and integration of new data hires in the Bengaluru office. • Over time, this role has the potential to evolve into a Center of Excellence (COE) model—becoming the single point of data leadership in India across multiple product pillars (e.g., Payments, Growth, Marketing), not just Risk. Responsibilities • Build, manage, and develop a high-performing, geographically distributed data team. • Define and drive the data roadmap in close partnership with product, engineering, and business stakeholders—ensuring analytical work is tightly coupled to business outcomes. • Establish and raise the bar on analytical rigor, experimentation frameworks, and data science best practices across the team. • Recruit and retain skilled data talent, crafting a compelling hiring narrative anchored in local leadership and craft excellence. • Champion a culture of technical excellence, intellectual curiosity, and operational discipline. • Collaborate with cross-functional partners and other data leaders globally to align priorities, share learnings, and maintain org-wide consistency. • Communicate insights, recommendations, and team progress clearly to senior leadership. Who you are We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. Minimum requirements • 10+ years of experience in data science, analytics, or a related quantitative field, with 3+ years in a people management role leading data scientists or analysts • Strong technical foundation in SQL, Python or R, statistical modeling, and experimentation design • Demonstrated ability to translate ambiguous business problems into structured analytical frameworks and actionable insights • Experience managing and developing individual contributor talent across multiple levels, including coaching, career pathing, and performance management • Excellent communication and stakeholder management skills—able to influence without authority across functions and time zones along with proven ability to drive alignment and execution across distributed, cross-functional teams Preferred qualifications • Advanced degree (M.S. or Ph.D.) in a quantitative discipline such as Statistics, Economics, Computer Science, Mathematics, or a related field • Experience working in the payments, fintech, or financial services industry • Prior experience building and scaling data teams in a high-growth environment—particularly standing up 0 → 1 functions or teams • Track record of being a builder who has personally architected the rituals, standards, hiring bar, and craft culture for a data team from the ground up • Familiarity with risk, verifications, or compliance-related data domains • Experience operating across Asia-Pacific markets and navigating the nuances of multi-region team management • Passion for developing others and creating environments where individual contributors do the best work of their careers
Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We're looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. Our work is broad and varied, influencing how our products work (e.g., understanding user needs, preventing fraud, or optimizing charge flows), how our business works (forecasting key outcomes, managing liquidity, and quantifying risk exposure), how our go-to-market motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between. We have a variety of Data Science roles and teams across Stripe and will seek to align you to the most relevant team based on your background. What you'll do We're looking for a variety of Data Scientists to partner with the Product, Finance, Payments, Security, Risk, Growth, and Go-to-Market teams. You'll work closely with a specific part of the business, playing a crucial role in optimizing our systems and leveraging data to make strategic business decisions. As Data Scientists at Stripe, it's our mission to ensure that the company strategy, products, and user interactions make smart use of our rich data, using techniques like machine learning, statistical modeling, causal inference, optimization, experimentation, and all forms of analytics. Who you are We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. Minimum requirements PhD with 3 years, MS or MA with 6 years, or BS or BA with 8 years of data science or quantitative modeling experience Proficiency in SQL and a computing language such as Python or R Experience in working with cross-functional teams to deliver results Ability to communicate results clearly and a focus on driving impact A demonstrated ability to manage and deliver on multiple projects with a high attention to detail Strong business acumen and experience in synthesizing complex analyses into actionable recommendations Proficiency with AI tools to accelerate model development, analysis, and coding Preferred qualifications Strong knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and experimentation Experience deploying models in production and adjusting model thresholds to improve performance Experience designing, running, and analyzing complex experiments or leveraging causal inference designs A builder's mindset with a willingness to question assumptions and conventional wisdom Experience with distributed tools such as Spark, Hadoop, etc. A PhD or MS in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)
Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team You’ll be joining the data science team at Stripe responsible for our overall infrastructure, with a focus on core systems and cloud platforms. Projects include, but are not limited to: Developing models to predict resource needs as Stripe demand increases; Working closely with engineers to improve the cost and performance of platforms and services; Employing quantitative methods to drive and automate fleet decisions. You will act as a key strategic data partner to the Core Infrastructure organization at Stripe, and help craft, guide, and drive the strategy and tactics needed to help ensure Stripe can continue to scale with efficiency and dependability as our business rapidly grows. What you'll do As a Data Scientist, your role will involve: Analyzing infrastructure usage, efficiency, and workloads to predict demand and inform capacity planning. Developing models and strategies for efficient compute resource consumption and provisioning. Collaborating with engineers, engineering leadership, and finance teams to ensure Stripe makes the right, data-driven, infrastructure decisions. Providing actionable insights and recommendations to improve infrastructure operations to reduce costs and improve reliability. Utilizing your analytical expertise to influence both technical and financial strategies within Stripe. Who you are We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. Location Requirement Seattle, WA or San Francisco, CA (Hybrid: 50% in office) Minimum requirements PhD with 3+ years, MS or MA with 6+ years, or BS or BA with 8+ years of data science or quantitative modeling experience. 3-8+ years of experience with a focus on infrastructure, cloud environments, and resource utilization/allocation. Proficiency in SQL and a computing language such as Python or R. Experience in analyzing logs/telemetry, scheduling optimization, or cloud infrastructure engineering. Ability to effectively work both independently and with cross-disciplinary teams, including engineering and finance, to deliver impactful results. A demonstrated ability to manage and deliver on multiple projects with a high attention to detail. Solid business acumen and experience in synthesizing complex analyses into actionable recommendations. A track record of building relationships with and influencing the decisions of senior technical leadership. A builder's mindset with a willingness to question assumptions and conventional wisdom. Preferred qualifications Background in deploying data models in production environments and optimizing their performance. Experience in using, deploying on, and analyzing usage data from public cloud providers. Familiarity with distributed computing tools such as Spark and Hadoop. A PhD or MS in a quantitative field like Computer Science & Engineering, Statistics, Mathematics, Operations Research, Industrial Engineering, Management Science, or related disciplines. Strong business acumen with a track record of translating complex data analyses into actionable business recommendations.
Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We're looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. Our work is broad and varied, influencing how our products work (e.g., understanding user needs, preventing fraud, or optimizing charge flows), how our business works (forecasting key outcomes, managing liquidity, and quantifying risk exposure), how our go-to-market motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between. We have a variety of Data Science roles and teams across Stripe and will seek to align you to the most relevant team based on your background. What you’ll do We’re looking for a Data Scientist to partner with our Global Growth teams. You’ll play a key role in designing and shipping experiments, as well as identifying improvement opportunities across stripe.com and the dashboard to help businesses worldwide get started on Stripe. You’ll help us understand, grow, and optimize the self-serve user funnel to ensure a consistently high-quality onboarding experience for users globally. As Data Scientists at Stripe, our mission is to ensure that company strategy, products, and user interactions make smart use of our rich data using techniques like machine learning, statistical modeling, causal inference, optimization, experimentation, and all forms of analytics. Who you are We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. Minimum requirements Bachelors + 8 years or Masters + 6 years or Phd + 3 years of data science or quantitative modeling experience Proficiency in SQL and a computing language such as Python or R Experience in working with cross-functional teams to deliver results Ability to communicate results clearly and a focus on driving impact A demonstrated ability to manage and deliver on multiple projects with a high attention to detail Strong business acumen and experience in synthesizing complex analyses into actionable recommendations Proficiency with AI tools to accelerate model development, analysis, and coding Preferred qualifications Strong knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and experimentation Experience deploying models in production and adjusting model thresholds to improve performance Experience designing, running, and analyzing complex experiments or leveraging causal inference designs A builder's mindset with a willingness to question assumptions and conventional wisdom Experience with distributed tools such as Spark, Hadoop, etc. A PhD or MSc in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)
Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We're looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. Our work is broad and varied, influencing how our products work (e.g., understanding user needs, preventing fraud, or optimizing charge flows), how our business works (forecasting key outcomes, managing liquidity, and quantifying risk exposure), how our go-to-market motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between. We have a variety of Data Science roles and teams across Stripe and will seek to align you to the most relevant team based on your background. What you’ll do We’re looking for a Data Scientist to partner with our Local Payment Methods (LPM) engineering and product teams. You’ll play a key role in understanding, growing, and optimising our LPM business, leveraging data to make strategic business decisions. As Data Scientists at Stripe, it's our mission to ensure that the company strategy, products, and user interactions make smart use of our rich data, using techniques like machine learning, statistical modeling, causal inference, optimization, experimentation, and all forms of analytics. Who you are We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. Minimum requirements PhD, MSc or MA with 2 years, or BS or BA with 3 years of data science or quantitative modeling experience Proficiency in SQL and a computing language such as Python or R Experience in working with cross-functional teams to deliver results Ability to communicate results clearly and a focus on driving impact A demonstrated ability to manage and deliver on multiple projects with a high attention to detail Strong business acumen and experience in synthesizing complex analyses into actionable recommendations Proficiency with AI tools to accelerate model development, analysis, and coding Preferred qualifications Strong knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and experimentation Experience deploying models in production and adjusting model thresholds to improve performance Experience designing, running, and analyzing complex experiments or leveraging causal inference designs A builder's mindset with a willingness to question assumptions and conventional wisdom Experience with distributed tools such as Spark, Hadoop, etc. A PhD or MSc in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)
About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the Team Deal Pricing is a dedicated global function that provides deal pricing expertise, financial insights, and deal support for negotiated users to Stripe's global Go-to-Market teams. We work to ensure deals create economic value for Stripe by establishing the deal commercial framework for a scaling sales organization, actively supporting large and strategic deals and providing pricing insights and feedback to sales, finance, and product leaders. Deal Pricing frequently works with cross-functional business partners across Operations, Finance and Strategy, and Product. There is constant collaboration with Deal Pricing colleagues across all regions. AMER Deal Pricing covers teams in the United States, Canada, and Latin America. Team members are located in Stripe offices and remote locations across the region. What You’ll Do You'll be instrumental in providing thought leadership to regional sales teams and senior executives and continuing to develop our framework, approach, and associated processes in order to achieve mutually beneficial deals with our sold Users while mitigating risk to Stripe. In addition to providing key financial insights and recommendations to business partners and Stripe leadership, you'll have a chance to stretch beyond the boundaries of finance through business case development and commercial negotiations with all types of customers across the full suite of Stripe's financial and payment products. Responsibilities Serve as a key financial and strategic thought partner to specific AMER Go-to-Market sales teams and their leadership in both pricing deals at scale and pricing strategic deals Be responsible for defining and implementing our pricing and margin guidance and identifying levers for financial uplift Develop and refine new frameworks to evaluate a deal's attractiveness to Stripe, ensuring alignment between these frameworks, the company's long-range plan, and mutually agreeable outcomes with cross-functional business partners Maintain up-to-date pricing benchmarks and contribute to team analytical design and production efforts, using this data to enhance our pricing philosophy Who You Are We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. Minimum Requirements 3+ years of experience in finance or deal pricing at a company, or experience within investment banking or management consulting A proven ability to build collaborative working relationships with business partners through a combination of influencing and awareness The ability to deal effectively with ambiguity and thrive in an unstructured, fast-moving environment by driving business results without significant supervision Excellent financial modeling, verbal and written communication skills Preferred Qualifications Experience in the payments or technology sector Experience presenting findings and recommendations to senior leadership, preferably to sales or go-to-market business partners Experience with SQL and Tableau or a willingness to learn is a must.
Who we are About Stripe Stripe, LLC. is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. What you’ll do Responsibilities Serve as a key financial and strategic thought partner to specific AMER go-to-market sales teams and their leadership in both pricing deals at scale and pricing strategic deals. Define and implement our pricing and margin guidance and identify levers for financial uplift. Develop and refine new frameworks to evaluate a deal’s attractiveness to Stripe, ensuring alignment between these frameworks, the company’s long-range plan and mutually agreeable outcomes with cross-functional business partners. Maintain up-to-date pricing benchmarks and contribute to team analytical design and production efforts, using this data to enhance our pricing philosophy. Who you are Minimum requirements Must have a Bachelor's degree or foreign equivalent in Finance, Business Administration, Economics, or a related field, plus three (3) years of experience in finance or deal pricing, investment banking, or management consulting. Must have three (3) years of experience with/in: Building collaborative working relationships with business partners, including incorporating financial model recommendations into findings, developing obstacle alternatives aligned with team goals as part of objection handling, and translating prior obstacles into actionable process and design improvements; Financial modeling using a spreadsheet-based tool; Payments or technology sector; Presenting findings and recommendations to senior leadership, including sales of go-to-market business partners; Data analysis of historical and projected financial data to identify trends or anomalies; and End-to-end process improvements as part of the deal-making process, including approvals, prioritization, formatting review, and cross-functional partner collaboration. Salary: $144,000 - $216,000/yr. This salary range represents the base salary range for the role and any sales commissions/sales bonuses targets, if applicable, would be in addition to the base salary. 40 hrs/week 50% Telecommuting permitted. Multiple positions available. Additional benefits for this role may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits; and wellness stipends. CA42 #LI-DNI